Search Results (67)

This study examines emotional dependency on generative artificial intelligence among vocational high school (VHS) students. Guided by Taiwan’s 108 Curriculum Guidelines, an interactive “Health and Nursing” course on AI reliance was implemented. The sample included 1000 students from five VHSs in central Taiwan (January–February 2026). Data were collected through questionnaires and classroom feedback to assess AI interaction frequency, emotional projection, and perceived effects on relationships and psychological needs. Research data were analyzed using SPSS 22.0 and SmartPLS 4. Findings show that some students displayed moderate to high emotional attachment to AI, particularly for support and stress relief, with blurred ethical boundaries. After the intervention, students reported greater awareness of risks and increased self-reflection. This study concludes that integrating AI literacy with emotional education into curricula is crucial for responsible technology use and healthy relational development. Overall, emotional reliance on AI among VHS students appears statistically significant but bounded, reflecting a balanced pattern of engagement that supports sustainable psychological well-being. Full article

Early literacy screening is essential for reducing long-term educational inequality, yet traditional paper-based assessments remain difficult to scale due to logistical constraints and delayed feedback. This study presents K-KOBUKI, a cloud-based prototype screening workflow that organizes early literacy assessment as a human-validated, data-driven process. The system integrates structured assessment responses with automated speech recognition-based analysis of oral reading performance across five literacy domains and incorporates a human-in-the-loop verification stage to ensure the reliability of speech-derived features. The system was evaluated using data from 195 first-grade students. Across repeated stratified cross-validation, multiple classification models achieved stable recall (≈0.85) under class imbalance conditions, supporting consistent identification of at-risk learners. Psychometric-informed feature refinement improved precision without reducing recall, indicating enhanced signal clarity through measurement-level stabilization. Explainable AI analysis further revealed that word reading and reading fluency contributed strongly to model-level decision boundaries, while vocabulary knowledge provided complementary influence at the individual level. These findings provide prototype-level evidence that a human-validated, multimodal screening workflow can support stable early-risk detection. From a sustainability perspective, the results suggest potential design-level contributions to improving accessibility and reducing delays in early identification processes. Full article

Non-alcoholic fatty liver disease affects approximately thirty percent of the global population, yet public awareness remains dangerously low among young adults facing occupational risk factors. This study introduces the Fatty Liver Awareness Game (FLAG), an educational serious game designed to improve liver health literacy among software engineering students at the University of Guayaquil. While evaluated with this specific sample, FLAG is intended for the broader target population of young adults in developing nations who face occupational sedentary risk and limited access to preventive health education. Through a controlled experiment with fifty participants randomly assigned to game-based or traditional lecture instruction, the game demonstrated superior effectiveness, with a twenty-percentage-point advantage in post-test scores and a seventy-two percent reduction in incorrect responses compared to fifty percent in the lecture group. The large effect size (Cohen’s d = 1.43) and reduced performance variability among game participants indicate that interactive, feedback-rich learning environments can outperform passive instruction for this population and content domain. While the present design does not isolate the contribution of individual game elements—such as narrative framing, explanatory feedback, or mini-game interleaving—the results establish FLAG as a replicable model for digital health interventions targeting underserved populations at critical developmental junctures. Future component analyses are needed to determine which specific design features drive the observed advantages. Full article

Background/Objectives: Nursing informatics competency is critical for nursing students entering clinical practice in the digital era. Current undergraduate nursing informatics courses prioritize theoretical instruction but lack sufficient integration with clinical applications, which restricts the depth of content delivery. This study aimed to design, implement, and conduct a preliminary evaluation of an undergraduate nursing informatics literacy course. Methods: This was a single-arm mixed-methods study. We implemented five sequential steps aligned with the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model: (1) needs assessment, (2) design of a systematic, progressive course spanning theoretical foundation, technical skills, and clinical application; (3) development of teaching materials and environment; (4) implementation through nine weekly 90 min sessions incorporating teach–practice–feedback; and (5) evaluation via a customized questionnaire and nursing informatics system project reports. Quantitative data were analyzed using the mean, standard deviation, and paired t tests; qualitative data were collected through post-course semi-structured interviews. Results: A total of 120 participants were enrolled from a provincial public medical school, of which 119 (99.2%) completed the course. Statistically significant pre–post improvements were observed in participants’ nursing informatics competencies, informatics literacy self-efficacy, and innovative behavior after course completion (p < 0.001). Participants completed 12 group projects, which received two C grades, nine B grades, and one A grade. Overall course satisfaction averaged 89.03 ± 14.62. Qualitative interviews yielded three themes: (a) cognitive reconstruction and improvement in the ability to apply nursing informatics competencies, (b) dilemmas and breakthroughs in the integration of technology and knowledge in nursing informatics design, and (c) optimization direction of course content, design, and evaluation. Conclusions: An ADDIE-based nursing informatics literacy course may be associated with improvements in nursing informatics competencies, informatics literacy self-efficacy, and innovative behavior among nursing undergraduates. This study provides preliminary evidence supporting the feasibility and potential educational value of such a curriculum. Full article

The incorporation of digital technologies has transformed Social Work, generating new demands in terms of professional competencies. It is worth questioning whether, in contexts as sensitive as social services, the mere acquisition of instrumental mastery of these tools is sufficient to ensure safe practice. Considering that the level of proficiency with these tools is influenced by age, the aim of this study is to conduct a comparative analysis of the digital competence levels of social work professionals and students in order to contrast the skills and shortcomings of both groups. To achieve this, a quantitative methodological design was employed using questionnaires based on the European DigComp 2.2 framework. The sample included 451 professionals from Spain and 171 students from the University of Huelva, whose data were processed using statistical software (SPSS 27). The results show that students display a higher overall level of digital competence, particularly in the creation of digital content and the use of artificial intelligence tools. Professionals, on the other hand, demonstrate stronger competencies in digital security and data literacy. The findings reveal a clear complementarity between the two groups, highlighting an opportunity for mutual feedback and learning that can help combine technological efficiency with ethical responsibility and respect for human rights. Full article

Background/Objectives: Periodontitis represents a significant global health burden, yet preventive health literacy remains critically low among emerging adults—a developmental stage where lifelong health behaviors crystallize. This study evaluated the effectiveness of the GUM (an acronym of Gum Understanding Mission) game, an interactive gamified digital tool incorporating AI-informed or manual feedback, for improving periodontitis literacy among tenth-semester Software Engineering students at the University of Guayaquil. Methods: In a controlled pre-test/post-test experiment, 50 participants were randomly assigned to either the GUM game intervention or a traditional lecture. Both groups completed identical knowledge assessments immediately before and after their respective 50-min instructional sessions. The GUM game featured adaptive questioning, immediate elaborated feedback, and comprehensive performance analytics, while the control group received instructor-led didactic instruction with a subsequent question-and-answer session. Results: The GUM group improved from a baseline of 21% to 94% correct responses, while the lecture group increased from 22% to 67% ($p<0.001$). Error reduction was 74% in the GUM group versus 45% in the control group. However, the study’s scope is currently limited to a single, digitally literate cohort, and knowledge retention over time was not assessed. Conclusions: These findings suggest that a self-directed, feedback-driven serious game can substantially outperform traditional methods in fostering periodontitis literacy within this population. Further research is needed across diverse populations with extended follow-up periods to assess knowledge retention and generalizability. Full article

Online asynchronous learning offers considerable flexibility but frequently faces challenges in sustaining engagement, interactivity, and inclusivity across diverse learner populations. This study introduces the OPTIMAL framework—an Online, Pedagogy- and Technology-Integrated, Microcurricula Approach for interactive and inclusive Learning—synthesising universal design for learning, active learning, and constructive alignment with technology integration frameworks (TPACK and PICRAT), operationalised through a microcurricula-as-a-service architecture. A three-year longitudinal case study (2022/23 to 2024/25) examined the application of the framework to a data literacy and analytics module serving over 5000 students across more than 15 programs and five faculties at Dublin City University. The module design constructively aligned learning outcomes, content, and technology at three levels to support multiple learning pathways, formative assessment, and transdisciplinary engagement, deliberately fostering transformative uses of technology in a fully asynchronous environment. Mixed-methods evaluation—combining learning analytics, surveys (n = 1743), and qualitative feedback—demonstrated sustained positive outcomes across all three years, including 95–99% completion rates, consistently high satisfaction, and longitudinal gains in engagement and pass rates. These findings demonstrate how the deliberate integration of pedagogical theory, technological frameworks, and modular curriculum architecture can deliver scalable, inclusive, and high-engagement online education, offering both a transferable, evidence-based model for educators and curriculum designers and longitudinal empirical validation for researchers. Full article

Generative Artificial Intelligence (GenAI) is transforming higher education in terms of pedagogy, student involvement, and academic management. This systematic literature review examines 30 peer-reviewed articles published from 2019 to 2025, adhering to PRISMA 2020 and Kitchenham’s methodologies. Descriptive and thematic analyses highlight five opportunities: (a) tailored and adaptive education; (b) deliberate fostering of critical thinking; (c) enhanced accessibility for varied learners; (d) teaching innovation via multimodal content development and feedback; and (e) collaborative methods that regard AI as a co-teacher. Four ongoing challenge categories also surface: (a) risks to academic integrity; (b) excessive dependence on GenAI that may hinder learner independence; (c) inconsistent faculty preparedness and change-management abilities; and (d) differences in infrastructure and policy both regionally and globally. Intersecting ethical issues, such as data privacy, algorithmic bias, transparency, and accountability, highlight the necessity for governance that aligns with institutional risk and reflects societal values. Analyzing the recent literature, this systematic review offers four contributions: (a) a recommendation model for responsible GenAI implementation in higher education institutions; (b) a framework for sustainable integration of GenAI; (c) a highlight of the future research recommendations; and (d) an integrated policy and pedagogical recommendations roadmap. These models emphasize the integration of AI literacy, ethical considerations, and critical thinking goals into educational programs. The review advocates for a strategic, stakeholder-focused approach to implementation that enhances rather than replaces human instruction, thus connecting GenAI’s educational potential with ethical, context-aware avenues for institutional transformation. Full article

The increasing integration of Generative AI (GenAI) into higher education, particularly in the domain of language teaching, presents both opportunities and challenges. While AI-powered tools such as ChatGPT-5 can support language learning by generating personalised content which enables real-time interaction and feedback, they also risk perpetuating biases embedded in training data. These biases can appear in linguistic, cultural or socio-political forms, reinforcing stereotypes and influencing language norms. Therefore, equipping students and educators with strategies to critically assess AI outputs is essential for ethical and responsible AI use in language education. While recent research highlights the risks of algorithmic bias, less attention has been given to the perceptions and attitudes of pre-service teachers, whose future practice will shape classroom uses of these technologies. This exploratory pilot study adopts a survey-based approach to examine pre-service teachers’ baseline awareness of bias in artificial intelligence, with particular attention to linguistic and cultural dimensions Data were collected through an online questionnaire administered to 65 undergraduate students enrolled in Primary Education degree programmes. The study documents baseline perceptions prior to any instructional intervention and provides preliminary empirical evidence to inform the future design of pedagogical strategies aimed at developing critical AI literacy in teacher education. Full article

Peer feedback is widely used in English as a foreign language (EFL) higher education, yet its benefits are often limited by uneven feedback quality and learners’ difficulty in interpreting and using comments. This theoretical paper synthesizes research on peer feedback, student feedback literacy, and recent developments in generative artificial intelligence (GenAI) to propose a theory-informed design framework that positions GenAI as Trainer and Synthesizer in L2 speaking peer feedback. Building on feedback literacy as a set of capacities (appreciating feedback, making judgments, managing affect, and taking action), the paper argues that speaking tasks create distinct constraints, including time pressure, fleeting performance, and heightened affect, which make real-time peer feedback promising but pedagogically challenging. To address these challenges, here we introduce two complementary roles for GenAI in peer feedback workflows: a Trainer that supports feedback quality through calibration with exemplars, rubric-guided practice, and feedback-on-feedback; and a Synthesizer that aggregates peer input into concise, actionable guidance linked to criteria and learning goals. The conceptual proposal specifies key design principles (e.g., transparency, learner agency, teacher-in-the-loop oversight, and privacy-conscious data practices) and outlines researchable propositions for evaluating learning, engagement, and equity outcomes. The paper concludes with implications for task design, training sequences, and responsible classroom implementation. Full article

Information visualization is a crucial yet often underdeveloped research skill in graduate education. This study examined how practice-based visualization instruction enhances graduate students’ conceptual understanding and procedural competence in scientific graph construction. Forty-two first-year graduate students participated in a ten-week instructional program combining diagnostic assessment, guided exercises, and a complex graph replication task. Conceptual and procedural competence were evaluated using validated analytic rubrics to ensure reliability and depth of analysis. Results showed substantial improvement in students’ ability to select suitable chart types, label axes accurately, and apply coherent color schemes. Consistent with the study’s hypotheses, significant gains were observed in conceptual understanding (H1) and technical execution (H2), and a moderate positive correlation between the two domains (H3) confirmed that stronger conceptual grasp aligned with higher visualization proficiency. Iterative feedback and guided reflection supported the integration of theory and practice. However, challenges in detailed annotation and multivariable coordination persisted. Overall, structured, practice-based visualization training enhanced methodological competence and communication clarity. Embedding such experiential learning within graduate curricula can strengthen visualization literacy and support the development of research independence. Full article

Authentic, situated learning experiences which mirror the collaborative nature of healthcare practice are essential in preparing students for their future professions. Feedback literacy may be thought of as the understanding, capacity, and disposition needed to make sense of information and use it to enhance work or learning strategies. This study explored how feedback literacy can be developed through situated, interprofessional peer-to-peer feedback within a community-based paediatric health screening programme. Using an exploratory Action Research qualitative design, the planning activities stage explored current practice, gathering student insights via interviews, reflections, and a workshop to co-design an Interprofessional Feedback Conversation Guide (IPFCG). The IPFCG was piloted, integrating structured feedback tools and protected time for peer exchange, within the community screening activity. Feedback regarding use of the IPFCG contributed to the gathering data stage, which was followed by the evaluation and reflection stage. Evaluation revealed four key themes: value, engagement, optimising relationships, and structuring conversations. Students valued receiving feedback from peers outside their discipline, actively engaged with the process, emphasised the importance of building rapport, and utilised structured dialogue. These findings highlight how authentic, field-based learning can foster feedback literacy, enhancing the development of professional identity. The interprofessional nature of the program reflects the complexity of modern healthcare and demonstrates how curriculum-integrated models of authentic learning can enhance student engagement and workplace readiness. This study contributes to the evolving conversation about embedding authenticity in higher education and offers a practical model for building collaborative communication within situated learning experiences at scale. Full article

The rapid transition to Industry 4.0/5.0 has widened the gap between graduates’ skill sets and labor market expectations; this study aimed to profile student competencies and align academic pathways with inclusive and adaptive AI-driven learning. A quantitative design was applied: an online survey of n = 126 students (engineering and economics, February–March 2025), expert evaluations from 5 faculty and 5 employers on a 5-point scale, framed by T-shaped competencies, 4C skills, and Bloom’s taxonomy. Analysis was performed in Python 3.11; future demand until 2035 was forecasted using ARIMA and Prophet models trained on publicly available labor market data (OECD, WEF, Eurostat 2015–2024); competency prioritization employed K-Means clustering and Random Forest models. Strengths included cooperation 4.2, critical thinking 3.9, communication 3.8, and creativity 3.6. Deficits were programming 2.8, project management 3.2, and solution development 3.2; employers rated programming at 2.5 (−0.7 compared to faculty). Forecast 2025–2035 showed growth in demand for programming +56% (3.2 → 5.0), data analytics +39% (3.6 → 5.0), project management +34% (3.2 → 4.3), digital literacy +30% (3.7 → 4.8), and critical thinking +15% (3.9 → 4.5). Clustering identified critical (programming, analytics, project management), supporting (creativity, communication, teamwork), and optional (narrow theoretical depth) competencies. Curriculum adjustment with practice-oriented modules, AI-enabled adaptive learning, and systematic university–employer feedback is essential; the proposed AI-supported profiling model is scalable and enhances inclusiveness. Full article

Feedback is an integral part of the learning process. However, delivering feedback effectively remains challenging, particularly within massified higher education systems that are characterised by large cohorts and increasingly diverse student populations. The emergence of generative artificial intelligence (GenAI) enables new ways of embedding feedback into educational offerings, some of which may be highly beneficial. In this paper, we introduce Abundant Feedback as a conceptual lens for examining the new capabilities that may be enabled by GenAI. We present a four-dimensional framework identifying the dimensions of GenAI feedback as abundance of Volume, of Availability, of Relevance and of Character. Through a systematic literature search, we describe how these dimensions manifest in recent empirical studies, and identify two educational domains, Computer Programming and Foreign Languages, as early adopters of AI-generated feedback. Beyond merely digitising existing scarce feedback processes, we discuss the emergence of new learner-driven feedback practices that are enabled by abundance, that both stimulate and demand student feedback literacy. Our multi-dimension abundance framework provides a lens, as well as the vocabulary and conceptual tools, to guide the implementation of GenAI feedback in ways that help realise the potential of artificial intelligence to enhance student learning. Full article

In response to problems inherent in conventional hydraulic engineering education including compartmentalized courses, fragmented knowledge delivery, overlapping and omitted content, and insufficient development of students’ integrated practical competencies this study develops an instructional model for a coordinated curriculum group based on the OBE-BOPPPS teaching theory. The curriculum cluster model aims to integrate interdisciplinary course content, restructure curriculum structure hierarchy, eliminate disciplinary barriers, and establish clear stratified and interrelated knowledge relationships. The model centers on competency development, constructing a three-dimensional “agent–objective” system that connects “teacher–student–curriculum” with “knowledge–competency–literacy.” It further establishes a multi-indicator evaluation system encompassing teachers, students, and courses. The comprehensive evaluation employing Principal Component Analysis, Entropy Weight Method, and CRITIC method demonstrates that the curriculum group teaching model significantly outperforms traditional course-based instruction in transcending disciplinary boundaries, enhancing knowledge systematicity, improving teaching precision, and strengthening knowledge acquisition as well as students’ comprehensive competencies. This approach achieves dynamic optimization and precision feedback in the teaching process, effectively facilitating the systematic transfer of knowledge and the holistic development of students’ innovative practical abilities. It thereby provides a scientific pathway and empirical support for the reform of hydraulic engineering education and the cultivation of high-quality talent. Full article